• Title/Summary/Keyword: 패턴확장기법

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Immediate Effect of Patterned Sensory Enhancement (PSE) on Upper Limb Function after Stroke (패턴화된 감각 증진(PSE)이 뇌졸중 환자의 상지 기능에 미치는 즉각적 영향)

  • Han, Soo Jeong;Kwon, Ae Ji;Park, Hye Young
    • Journal of Music and Human Behavior
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    • v.11 no.1
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    • pp.1-19
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    • 2014
  • The purpose of this study was to investigate the immediate effect of Patterned Sensory Enhancement (PSE) technique on the motor function of the affected upper limb in hemiplegic stroke patients by comparing the use of PSE and simple rhythmic cue. A total of 16 stroke patients were recruited from rehabilitative hospitals. The participants were assigned to the experimental group (n = 8) and control group (n = 8). While performing six different upper limb motions, musical stimuli applying the PSE technique was presented for the experimental group and simple rhythmic cue using the metronome was applied for the control group. The results showed that while the significantly increased range of motion (ROM) was found in the experimental group with the immediate use of PSE (p < .05), the control group did not show no significant change. This study implies that the use of musical elements in cueing for upper limb motion immediately leads to significant improvement in ROM by providing sufficient temporal, spatial, and dynamic information for expected motor performance.

A Recursive Procedure for Mining Continuous Change of Customer Purchase Behavior (고객 구매행태의 지속적 변화 파악을 위한 재귀적 변화발견 방법)

  • Kim, Jae-Kyeong;Chae, Kyung-Hee;Choi, Ju-Cheol;Song, Hee-Seok;Cho, Yeong-Bin
    • Information Systems Review
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    • v.8 no.2
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    • pp.119-138
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    • 2006
  • Association Rule Mining has been successfully used for mining knowledge in static environment but it provides limited features to discovery time-dependent knowledge from multi-point data set. The aim of this paper is to develop a methodology which detects changes of customer behavior automatically from customer profiles and sales data at different multi-point snapshots. This paper proposes a procedure named 'Recursive Change Mining' for detecting continuous change of customer purchase behavior. The Recursive Change Mining Procedure is basically extended association rule mining and it assures to discover continuous and repetitive changes from data sets which collected at multi-periods. A case study on L department store is also provided.

Intelligent provisioning service using ontology (온톨로지를 이용한 지능형 프로비저닝 서비스)

  • Jeong, Hoon;Kim, Nanju;Pyo, Hyejin;Choi, Euiin
    • Journal of Digital Convergence
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    • v.12 no.5
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    • pp.239-247
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    • 2014
  • Ubiquitous computing environment, as a new paradigm of the digital information era, has been introduced to respond to rapid changes in society and culture. Today, technology research around the world competes for the preoccupancy of the core technology as well as the development of technology for providing context aware system more intelligent, more sophisticated. Research in recent is underway the implementation of intelligent provisioning system using the ontology. Erstwhile provisioning system did not providing a personalized service that provides the service after context aware. Accordingly, there is a need for studies of intelligent context aware provisioning technique considering environments and context necessary to user. In this paper, in order to provide a service that is optimized for the needs of the user, propose an ontology-based intelligent provisioning service method taking into account the usage patterns and the context of the user. The proposed system is recognized the status of the user and demonstrated a process of reasoning techniques for fit service. And it is possible to the expansion of intelligence.

Multi-Document Summarization Method Based on Semantic Relationship using VAE (VAE를 이용한 의미적 연결 관계 기반 다중 문서 요약 기법)

  • Baek, Su-Jin
    • Journal of Digital Convergence
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    • v.15 no.12
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    • pp.341-347
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    • 2017
  • As the amount of document data increases, the user needs summarized information to understand the document. However, existing document summary research methods rely on overly simple statistics, so there is insufficient research on multiple document summaries for ambiguity of sentences and meaningful sentence generation. In this paper, we investigate semantic connection and preprocessing process to process unnecessary information. Based on the vocabulary semantic pattern information, we propose a multi-document summarization method that enhances semantic connectivity between sentences using VAE. Using sentence word vectors, we reconstruct sentences after learning from compressed information and attribute discriminators generated as latent variables, and semantic connection processing generates a natural summary sentence. Comparing the proposed method with other document summarization methods showed a fine but improved performance, which proved that semantic sentence generation and connectivity can be increased. In the future, we will study how to extend semantic connections by experimenting with various attribute settings.

Probabilistic Seepage Analysis Considering the Spatial Variability of Permeability for Layered Soil (투수계수의 공간적 변동성을 고려한 층상지반에 대한 확률론적 침투해석)

  • Cho, Sung-Eun
    • Journal of the Korean Geotechnical Society
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    • v.28 no.12
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    • pp.65-76
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    • 2012
  • In this study, probabilistic analysis of seepage through a two-layered soil foundation was performed. The hydraulic conductivity of soil shows significant spatial variations in different layers because of stratification; further, it varies on a smaller scale within each individual layer. Therefore, the deterministic seepage analysis method was extended to develop a probabilistic approach that accounts for the uncertainties and spatial variation of the hydraulic conductivity in a layered soil profile. Two-dimensional random fields were generated on the basis of the Karhunen-Lo$\grave{e}$ve expansion in a manner consistent with a specified marginal distribution function and an autocorrelation function for each layer. A Monte Carlo simulation was then used to determine the statistical response based on the random fields. A series of analyses were performed to verify the application potential of the proposed method and to study the effects of uncertainty due to the spatial heterogeneity on the seepage behavior of two-layered soil foundation beneath water retaining structure. The results showed that the probabilistic framework can be used to efficiently consider the various flow patterns caused by the spatial variability of the hydraulic conductivity in seepage assessment for a layered soil foundation.

An Service oriented XL-BPMN Metamodel and Business Modeling Process (서비스 지향 XL-BPMN 메타모델과 비즈니스 모델링 프로세스)

  • Song, Chee-Yang;Cho, Eun-Sook
    • KIPS Transactions on Software and Data Engineering
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    • v.2 no.4
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    • pp.227-238
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    • 2013
  • The business based existing BPMN model is a lack of service oriented modeling techniques. Therefore, it requires a layered technique of service oriented business modeling so that can meet the design for a complex application system, developing a system based on SOA. In order to enhance reusability and modularity of BPMN business model, this paper proposes a metamodel and business modeling process based on this metamodel that can hierarchically build a BPMN model. Towards this end, the XL-BPMN metamodel hierarchically established based on MDA and MVS styles are first defined. Then a BPMN service modeling process is constructed based on modeling elements of this metamodel according to the modeling phases. Finally, the result of a case study in which the proposed method is applied to an online shopping mall system is discussed. With the use of well-defined metamodel and modeling process, it is hoped that it can be shown that a service dominated and layered BPMN business model can be established, and that the modularity and reusability of the constructed BPMN business model can be maximized.

Personalized Recommendation System using FP-tree Mining based on RFM (RFM기반 FP-tree 마이닝을 이용한 개인화 추천시스템)

  • Cho, Young-Sung;Ho, Ryu-Keun
    • Journal of the Korea Society of Computer and Information
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    • v.17 no.2
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    • pp.197-206
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    • 2012
  • A exisiting recommedation system using association rules has the problem, such as delay of processing speed from a cause of frequent scanning a large data, scalability and accuracy as well. In this paper, using a Implicit method which is not used user's profile for rating, we propose the personalized recommendation system which is a new method using the FP-tree mining based on RFM. It is necessary for us to keep the analysis of RFM method and FP-tree mining to be able to reflect attributes of customers and items based on the whole customers' data and purchased data in order to find the items with high purchasability. The proposed makes frequent items and creates association rule by using the FP-tree mining based on RFM without occurrence of candidate set. We can recommend the items with efficiency, are used to generate the recommendable item according to the basic threshold for association rules with support, confidence and lift. To estimate the performance, the proposed system is compared with existing system. As a result, it can be improved and evaluated according to the criteria of logicality through the experiment with dataset, collected in a cosmetic internet shopping mall.

A Development Method of Framework for Collecting, Extracting, and Classifying Social Contents

  • Cho, Eun-Sook
    • Journal of the Korea Society of Computer and Information
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    • v.26 no.1
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    • pp.163-170
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    • 2021
  • As a big data is being used in various industries, big data market is expanding from hardware to infrastructure software to service software. Especially it is expanding into a huge platform market that provides applications for holistic and intuitive visualizations such as big data meaning interpretation understandability, and analysis results. Demand for big data extraction and analysis using social media such as SNS is very active not only for companies but also for individuals. However despite such high demand for the collection and analysis of social media data for user trend analysis and marketing, there is a lack of research to address the difficulty of dynamic interlocking and the complexity of building and operating software platforms due to the heterogeneity of various social media service interfaces. In this paper, we propose a method for developing a framework to operate the process from collection to extraction and classification of social media data. The proposed framework solves the problem of heterogeneous social media data collection channels through adapter patterns, and improves the accuracy of social topic extraction and classification through semantic association-based extraction techniques and topic association-based classification techniques.

SITM Attacks on Skinny-128-384 and Romulus-N (Skinny-128-384와 Romulus-N의 SITM 공격)

  • Park, Jonghyun;Kim, Jongsung
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.32 no.5
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    • pp.807-816
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    • 2022
  • See-In-The-Middle (SITM) is an analysis technique that uses Side-Channel information for differential cryptanalysis. This attack collects unmasked middle-round power traces when implementing block ciphers to select plaintext pairs that satisfy the attacker's differential pattern and utilize them for differential cryptanalysis to recover the key. Romulus, one of the final candidates for the NIST Lightweight Cryptography standardization competition, is based on Tweakable block cipher Skinny-128-384+. In this paper, the SITM attack is applied to Skinny-128-384 implemented with 14-round partial masking. This attack not only increased depth by one round, but also significantly reduced the time/data complexity to 214.93/214.93. Depth refers to the round position of the block cipher that collects the power trace, and it is possible to measure the appropriate number of masking rounds required when applying the masking technique to counter this attack. Furthermore, we extend the attack to Romulus's Nonce-based AE mode Romulus-N, and Tweakey's structural features show that it can attack with less complexity than Skinny-128-384.

Minimalism in Modern Hairstyle and Fashion (현대 헤어스타일과 의상에 나타난 미니멀리즘의 양상)

  • Sohn Hyang-Mi;Park Kil-Soon
    • Journal of the Korean Society of Clothing and Textiles
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    • v.29 no.12 s.148
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    • pp.1554-1561
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    • 2005
  • This study aims to analyze modern hairstyle and fashion in the collections in the late 1990s, based on the concepts and characteristics of Minimalism, a buzzword of the art field in the 1960s. This study used qualitative research method, in other words, presenting an analysis framework by studying domestic and foreign books and dissertations on Minimalism and then applying the Internet or visual image to the analysis framework. The result indicates that Minimalism design in modem hairstyle and fashion has four characteristics: simplicity, unity, repetition and spatiality.